class_docstr: Mutate the input choice nodes.
code: def mutate(self, model: GraphModelSpace) -> None:
      n_candidates = self.nodes[0].operation.parameters["n_candidates"]
      n_chosen = self.nodes[0].operation.parameters["n_chosen"]
      candidates = list(range(n_candidates))
      if n_chosen is None:
          chosen = [i for i in candidates if self.choice([False, True])]
          # FIXME This is a hack to make choice align with the previous format
          self._cur_samples = chosen
      else:
          chosen = [self.choice(candidates) for _ in range(n_chosen)]
      for node in self.nodes:
          target = cast(Node, model.get_node_by_name(node.name))
          target.update_operation(
              "__torch__.nni.nas.nn.pytorch.ChosenInputs",
              {
                  "chosen": chosen,
                  "reduction": node.operation.parameters["reduction"],
              },
          )
  
imports: from __future__ import annotations
  from typing import Any, List, Tuple, Dict, Iterable, cast
  from nni.mutable import MutableExpression, Categorical, frozen_context, label_scope
  from nni.nas.space import Graph, GraphModelSpace, Node, StationaryMutator, Mutator
  from nni.nas.space.graph_op import Cell
label_desc: Use image node_id 2 for calling the InputChoiceMutator obj's underlying member method code with example usage: obj.mutate(model) without return types